Decompose your case value into medical specials, lost wages, pain and suffering, and future damages.
Decompose case value into past + future medical, lost wages, and pain & suffering. Future amounts discounted to present value.
| Past medical | $28,500 |
| Future medical (PV) | $34,552 |
| Past lost wages | $12,500 |
| Future wage loss (PV) | $41,583 |
| Economic subtotal | $117,135 |
| Pain & suffering (3x medicals) | $189,156 |
| Total case value | $306,291 |
Decompose your case value into medical specials, lost wages, pain and suffering, and future damages.
Toggle pain-and-suffering multiplier between 1x and 5x to see how case value scales with injury severity. Each multiplier choice cites the case-law support.
Reduced-to-present-value calculations using 3-5% discount rate, age-tabled life expectancy, state-specific multipliers for pain and suffering based on PACER-observed verdict patterns.
The model produces a result paired with a reasoning trace and a list of cited sources. The reasoning trace is the actual analytical scratch pad the model used to arrive at the conclusion , not a marketing summary. You can audit the reasoning, verify it against the cited sources, and override the result if you disagree with how the model weighted a particular factor.
This approach is harder to build than a single-pass AI output, but it is the only way to publish AI-assisted personal-injury content responsibly. Personal-injury claims are a Your Money or Your Life (YMYL) topic under Google's quality framework. Outputs that cannot be audited or verified fail the EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) standard and should not be relied on.
Five-bucket itemization: past medical, future medical (NPV), past lost wages, future earning-capacity loss (NPV), pain and suffering (multiplier-based with sensitivity range). Total with state-specific cap notes.
Output is rendered with the same UI contract every tool on this site shares: a clearly labeled result, a "Show my reasoning" expander, source citations on every factual claim, the model used, and the timestamp of the last source verification. You can copy the output to clipboard, export to a Word-compatible document, or share a permalink that regenerates the same result on demand.
Sources are refreshed daily through a hash-compare verification pipeline. When a statute is amended, an appellate decision is published, or a primary-source database is updated, the tool flags the change within 24 hours and rebuilds any affected outputs.
This tool helps you understand the framework of a personal-injury case. It does not provide legal advice. It does not create an attorney-client relationship. The output is a starting point for a conversation with a licensed attorney in your state, not a substitute for one. Cases turn on facts the tool does not see; an attorney can.
General-purpose AI assistants and search engines can answer many personal-injury questions in a generic way. They cannot do what this tool does: combine the user's specific facts with the controlling state law and a verifiable primary-source database, then produce an auditable result. The reasoning trace is the difference: with a general AI assistant, you get an answer; with Damages Estimator, you get an answer plus a record of why.
For a $5,000 fender-bender case, that distinction may not matter much. For a $500,000 catastrophic-injury case, it matters enormously. The tools on this site are built for the second kind of case, not the first.
Every tool on this site has known limits, and Damages Estimator is no exception. The tool produces informational outputs based on the inputs you provide and the primary sources we have indexed. It does not see the facts an attorney would learn from interviewing you, reviewing your medical records, deposing the at-fault driver, or evaluating the strength of available witnesses. A tool that does not see those facts cannot replace an attorney who does.
The tool also cannot weigh the strategic value of the specific judge, opposing counsel, or local court culture that an experienced attorney handles intuitively. Damages Estimator produces a defensible baseline that is more accurate than guessing and more transparent than a defense-side analytics product. It is a starting point for a conversation with counsel, not the final word on your case.
Finally, the tool reflects the state of the primary-source database at the time of the last verification run. Statutes amend, appellate decisions reshape doctrine, and carrier behavior shifts in response to regulatory action. Damages Estimator updates its source data daily through the hash-compare freshness pipeline, but there is always a gap between a real-world change and the tool reflecting it. Verify time-sensitive output against the cited primary source before acting on it.
Damages Estimator is one of 12 AI-assisted tools on this site, each designed to address a specific decision a personal-injury plaintiff faces. The tools share a common contract: explainable result, reasoning trace, source citations, model and timestamp disclosed. They also share a common philosophy: AI for analytical reasoning, deterministic algorithms for monetary calculations, primary-source data for facts. The combination is more accurate than any single layer and more transparent than the defense-side analytics products that carriers have used for two decades.
Plaintiffs typically use Damages Estimator in combination with other site tools depending on case phase. Early in a case, the SOL Countdown and Case Value AI are the most useful , they establish the filing deadline and a defensible settlement range. Mid-case, the Demand Letter Generator and Insurance Playbook help structure the negotiation. Late-case, the Lawyer Cost Calculator and Settlement Tracker help evaluate offers and contribute anonymized data to help future plaintiffs. The tools compose; they do not replace each other.
Yes. All 12 tools on this site are free, with no email gate, no phone gate, and no required account. We do not refer cases to specific attorneys and do not accept referral fees.
deterministic + claude-opus-4-7. Claude verifies the inputs against PACER medians.
The output is informational and should never be relied on without verifying the cited sources and consulting an attorney licensed in your state. Every output includes the cited sources so you can verify the model's reasoning yourself. Personal-injury claims are a YMYL topic and require human judgment.
Source data is refreshed daily through a hash-compare verification pipeline. When a statute is amended or new appellate authority is published, the affected outputs are flagged and rebuilt within 24 hours.
No. Inputs are processed in your browser or in an ephemeral server function and are not stored, sold, or shared. We do not sell user data to claims-buyer firms, attorney-referral services, or marketing aggregators.